Abstract
With the ongoing crisis of biodiversity loss and limited resources for conservation, the concept of biodiversity hotspots has been useful in determining conservation priority areas. However, there has been limited research into how temporal variability in biodiversity may influence conservation area prioritization. To address this information gap, we present an approach to evaluate the temporal consistency of biodiversity hotspots in large marine ecosystems. Using a large scale, public monitoring dataset collected over an eight year period off the US Pacific Coast, we developed a methodological approach for avoiding biases associated with hotspot delineation. We aggregated benthic fish species data from research trawls and calculated mean hotspot thresholds for fish species richness and Shannon’s diversity indices over the eight year dataset. We used a spatial frequency distribution method to assign hotspot designations to the grid cells annually. We found no areas containing consistently high biodiversity through the entire study period based on the mean thresholds, and no grid cell was designated as a hotspot for greater than 50% of the time-series. To test if our approach was sensitive to sampling effort and the geographic extent of the survey, we followed a similar routine for the northern region of the survey area. Our finding of low consistency in benthic fish biodiversity hotspots over time was upheld, regardless of biodiversity metric used, whether thresholds were calculated per year or across all years, or the spatial extent for which we calculated thresholds and identified hotspots. Our results suggest that static measures of benthic fish biodiversity off the US West Coast are insufficient for identification of hotspots and that long-term data are required to appropriately identify patterns of high temporal variability in biodiversity for these highly mobile taxa. Given that ecological communities are responding to a changing climate and other environmental perturbations, our work highlights the need for scientists and conservation managers to consider both spatial and temporal dynamics when designating biodiversity hotspots.
Highlights
As global biodiversity loss continues at an unprecedented rate [1], protection of vulnerable species and ecosystems is of paramount concern
The biodiversity levels used to identify hotspots are often user-defined or set at arbitrary thresholds that are rarely based on long-term ecological data [22]. To address these issues of temporal disregard and subjectivity in hotspot designation, we present an objective approach for identifying biodiversity hotspots via a case study, wherein the assessment of temporal variability in biodiversity was integrated into the identification of candidate hotspots
Our objective was to determine the degree of temporal variability in biodiversity hotspots across the California Current Large Marine Ecosystem (CCLME) and contribute to the rapidly evolving concept of biodiversity hotspots
Summary
As global biodiversity loss continues at an unprecedented rate [1], protection of vulnerable species and ecosystems is of paramount concern. Dispersal and migratory patterns may encompass broad geographic regions, or cross ecological boundaries, with the potential for significant inter- and intra-annual fluctuations in local community structure and function [14,15,16,17] While these patterns are largely observable, anthropogenic drivers of biodiversity change (e.g. habitat alteration, overexploitation, introduction of exotic species, and climate change) fluctuate in both occurrence and intensity through time and are predicted to disrupt this synchrony in nature [18]. Climate models predict increased variability and frequency of climatic extremes over multiple time-scales, from changes that are sudden (occurring in less than five years), to changes in climate over the century [19] This variability is expected to drive shifts in species’ distributions and, the composition of ecological communities [12,20]. For ecosystems that are inherently driven by cyclical or periodic variation in the environment, this continuous change may result in future no-analog conditions [21]
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